Scheduler systems typically utilize a model of a manufacturing process, such as a process to manufacture product A and product B, to calculate or determine an optimal manufacturing schedule. A user, such as an industrial engineer and a factory administrator, may perform an analysis of the process tool behavior before implementing a scheduler system to create a model of the process. Data is collected to analyze process tool behavior, but the collected data is typically a small amount of data and the data is collected at a high level. The data, therefore, does not provide sufficient granularity to enable a user to gain a more accurate analysis of process tool behavior. In addition, the data is collected at some point in time, and the model, therefore, is valid for that point in time. However, process tool behavior changes (e.g., equipment drift) and processes change (e.g., recipe changes), and the models are not capable of reflecting these changes since the model is based on data collected at an earlier point in time.